Fast heat transfer simulation for laser powder bed fusion
Fast heat transfer simulation for laser powder bed fusion
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DOI：
10.1016/j.cma.2023.116107
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发表时间：
2023-07
影响因子：
7.2
通讯作者：
Xiaohan Li;N. Polydorides
中科院分区：
文献类型：
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作者：
Xiaohan Li;N. Polydorides
激光粉末床熔融过程中温度分布和相变的准确快速建模是实现其质量保证的一个重要里程碑。通常被称为数字孪生技术，其目标是找到敏捷，快速计算，但也足够准确的模拟器，可以复制3D打印过程，同时提高其结果的质量。在这项工作中，我们提出了一个代理模型的非线性热传递方程耦合子空间投影和随机草图，利用有限元时域模拟的准确性和可解释性与蒙特卡罗采样的计算效率，适用于激光粉末床融合的模态。专注于解决从有限元近似和控制方程中的非线性赋予的高维性，我们的代理依赖于低维投影与子空间选择，随后子采样的Picard迭代用于求解投影的非线性方程组。在模拟过程中，通过结合先前的温度分布和局部部署的各向异性高斯函数来生成投影基，而草图绘制过程利用基于近似最优采样分布的高效采样而无需替换。投影和草图都被设计成与打印过程一起实现，这使得所提出的替代物能够处理不同的过程参数，而不需要离线的先前计算。一系列的数值实验，以验证代理的准确性和减少计算时间相比，高保真有限元模拟。虽然实现的加速可以高达10倍，但计算时间仍然与实时计算所需的时间相差几个数量级。所提出的方法允许处理不同的打印属性（激光功率和扫描速度）和任意的热导率各向异性。
Accurate and fast modeling of the temperature distribution and phase transitions in laser powder bed fusion is a major milestone in achieving its quality assurance. Commonly referred to as digital twin technology, the goal is to find agile, fast-to-compute but also sufficiently accurate simulators that can replicate the 3D printing process while enhancing the quality of its outcomes. In this work, we propose a surrogate model for the nonlinear heat transfer equation coupled with subspace projection and randomized sketching, that exploits the accuracy and explainability of finite element time-domain simulation with the computational efficiency of Monte Carlo sampling, applied to the modality of laser powder bed fusion. Focusing on tackling the high-dimensionality imparted from the finite element approximation and the nonlinearity in the governing equations, our surrogate relies on low-dimensional projection with subspace selection and subsequently sub-samples the Picard iterations utilized to solve the projected non-linear system of equations. The projection bases are generated in the process of simulation by combining previous temperature profiles and locally deployed anisotropic Gaussian functions, while the sketching process utilizes efficient sampling without replacement based on approximate optimal sampling distributions. Both the projection and the sketching are designed to implement alongside the printing process, which makes the proposed surrogate capable of handling different process parameters without requiring prior computations offline. A series of numerical experiments are presented to validate the surrogate’s accuracy and reduction in compute time compared to high-fidelity finite element simulations. Although the achieved speed-up can be as a high ten, computational times are still orders of magnitude away from what would be required for real-time computations. The presented methodology allows to handle different printing attributes (laser power and scan speed) and arbitrary thermal conductivity anisotropy.